Datacenters in which a large volume of data is stored in arrays of servers, secured and routed present any number of particular problems for asset management, such as managing network connectivity and balancing the assets within the datacenter in relation to heat dissipation and power consumption. Localised hotspots within the datacenter can lead to degraded performance of servers and also server failure. Similarly, localised high power consumption can lead to overloading of the datacenter's power supply network, resulting in server down time.
These problems become more pronounced where there are a number of different workgroups operating within one datacenter, for example in an outsourced datacenter where multiple third party organisations store their data. Each workgroup will have both common and client specific aims. This leads to a situation where there is no overall strategy, or centralised management technique, in place to ensure the smooth and synergistic operation of the datacenter.
The above mentioned problems demonstrate that there are a number of interrelated factors that need to be monitored and ideally optimised in order to maintain the reliable operation and longevity of data centre assets.
No prior solutions to these problems have been provided and simple tools such as network discovery tools were all that was provided in order to try and determine the contents of a datacenter.
The lack of tracking of assets within a datacenter and the autonomy of workgroups leads to a situation where the location of a particular asset, e.g. a server, is not known. Also, cabinet space is not actively managed, which in combination with the lack of tracking of assets leads to space within cabinets of the datacenter being assigned on the basis of arbitrary, or semi-arbitrary, decisions rather than attempting to optimise the use of cabinet space, and the distribution of heat load and power consumption.